Sequence generation is the method of assigning participants to their study groups. When individuals are assigned to their groups in a random order, there is a better chance that the groups being compared will be balanced with respect to participant characteristics that might be relevant to the study (i.e., confounders) - those that are known in advance, as well as those that are not. Balanced groups help to minimize selection bias ("systematic differences between baseline characteristics of the groups that are compared" [Higgins].
Random assignment includes methods that prevent anticipation of the order of allocation. Examples of adequate methods are the use of a computer-generated random number sequence or a random number table. Examples of non-random methods are alternation/rotation or assignment based on a predictable rule, like date of birth or medical record number.
Tools
Appropriate means of generating a random sequence:
Referring to a random number table (see link to example below)
Using a computer random number generator (see examples of programs below)
Creating random numbers: A number of stats programs will allow you to generate random numbers. When using this technique, it is necessary to have an a priori classification system that will be used to assign individuals to the different treatment groups. For example, using a program like Excel will allow you to generate random numbers between 0 and 1, and you may decide that any individuals with numbers <0.5 will be assigned to Group A and any individuals with numbers >=0.5 will be assigned to Group B.
On this page we've compiled a number of examples of risk of bias assessments - the good, the bad, and those that are a bit unclear. Feel free to work through them yourself and come up with an assessment oflow,unclear, orhighrisk of bias (our judgments and rationale are on theassessments page), or download a spreadsheet file with the same information. RoB assessments are divided up into the seven major domains: sequence generation, allocation concelment, blinding of participants/personnel, blinding of outcome assessors, incomplete outcome data, selective outcome reporting, and other sources of bias. A quotation is given with the article title following in brackets.
If you have other examples, please add them to the list!
Altman DG, Bland JM. How to randomise. BMJ 1999; 319:703-704. [PubMed]
Als-Nielsen B, Gluud LL, Gluud C. Methodological quality and treatment effects in randomised trials: a review of six empirical studies. 12th Cochrane Colloquium 2004;Oct 2-6 (Ottawa, Ontario, Canada). [Cochrane]
What is sequence generation?
Table of Contents
Random assignment includes methods that prevent anticipation of the order of allocation. Examples of adequate methods are the use of a computer-generated random number sequence or a random number table. Examples of non-random methods are alternation/rotation or assignment based on a predictable rule, like date of birth or medical record number.
Tools
Appropriate means of generating a random sequence:
Random number table: The WHO gives an example of a random number table and instructions for its use.
Creating random numbers: A number of stats programs will allow you to generate random numbers. When using this technique, it is necessary to have an a priori classification system that will be used to assign individuals to the different treatment groups. For example, using a program like Excel will allow you to generate random numbers between 0 and 1, and you may decide that any individuals with numbers <0.5 will be assigned to Group A and any individuals with numbers >=0.5 will be assigned to Group B.
A nice tutorial with screen shots for generating randomization sequences in Excel and SPSS can be found at: http://www.itu.dk/courses/DEDA/F2010/ExerciseHandoutsRessources/RandomisationInExcelAndSPSS.pdf
Various options for creating random sequences in SAS are provided at: http://www2.sas.com/proceedings/sugi27/p267-27.pdf
The syntax for various programs is provided below:
- Microsoft Excel: =rand() [to generate a random number between 0 and 1]
- Microsoft Excel: =randbetween(x,y) [to generate a random integer number between the numbers (x,y) you specify]
- Stata: gen x = runiform()
- R or S-Plus: random.seed
- runif(n, min=0, max=1)
Randomization services: There are also online services that can create your randomization sequence. Some examples are provided below.Clinical trials coordinating centres may also offer randomization services.
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Examples
On this page we've compiled a number of examples of risk of bias assessments - the good, the bad, and those that are a bit unclear. Feel free to work through them yourself and come up with an assessment of low, unclear, or high risk of bias (our judgments and rationale are on the assessments page), or download a spreadsheet file with the same information. RoB assessments are divided up into the seven major domains: sequence generation, allocation concelment, blinding of participants/personnel, blinding of outcome assessors, incomplete outcome data, selective outcome reporting, and other sources of bias. A quotation is given with the article title following in brackets.
If you have other examples, please add them to the list!
Risk of Bias Guidelines
Download examples:
[back to top] [RoB Assessment Page]
References
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